ulysses paulino albuquerque reinaldo farias paiva de...

Methods and Techniques in Ethnobiology and Ethnoecology

Ulysses Paulino AlbuquerqueReinaldo Farias Paiva de LucenaLuiz Vital Fernandes Cruz da CunhaRômulo Romeu Nóbrega Alves Editors

Second Edition

Methods and Techniques

in Ethnobiology and Ethnoecology

Second Edition

Edited by

Ulysses Paulino Albuquerque

Departamento de Botânica, Universidade Federal de Pernambuco, Recife, Brazil

Reinaldo Farias Paiva de Lucena

Departamento de Sistemática e Ecologia, Universidade Federal da Paraiba, João Pessoa, Paraíba,

Brazil

Luiz Vital Fernandes Cruz da Cunha

Departamento de Ciências Biológicas, Universidade Católica de Pernambuco, Recife, Brazil

Rômulo Romeu Nóbrega Alves

Departamento de Biologia, Universidade Estadual da Paraíba, Campina Grande, Brazil

Editors

Ulysses Paulino AlbuquerqueDepartamento de BotanicaUniversidade Federal de PernambucoRecife, Brazil

Reinaldo Farias Paiva de LucenaDepartamento de Sistematica e EcologiaUniversidade Federal da ParaibaJoao Pessoa, Paraıba, Brazil

Luiz Vital Fernandes Cruz da CunhaDepartamento de Ciencias BiologicasUniversidade Catolica de PernambucoRecife, Brazil

Romulo Romeu Nobrega AlvesDepartamento de BiologiaUniversidade Estadual da ParaıbaCampina Grande, Brazil

ISSN 1949-2448 ISSN 1949-2456 (electronic)Springer Protocols HandbooksISBN 978-1-4939-8918-8 ISBN 978-1-4939-8919-5 (eBook)https://doi.org/10.1007/978-1-4939-8919-5

Library of Congress Control Number: 2018959858

© Springer Science+Business Media, LLC, part of Springer Nature 2019This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material isconcerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproductionon microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation,computer software, or by similar or dissimilar methodology now known or hereafter developed.The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply,even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulationsand therefore free for general use.The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed tobe true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty,express or implied, with respect to the material contained herein or for any errors or omissions that may have been made.The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This Humana Press imprint is published by the registered company Springer ScienceþBusiness Media, LLC part ofSpringer Nature.The registered company address is: 233 Spring Street, New York, NY 10013, U.S.A.

Chapter 10

The Spatiotemporal Scale of Ethnobiology: A ConceptualContribution in the Application of Meta-Analysis and theDevelopment of the Macro-Ethnobiological Approach

Tania Vianney Gutierrez-Santillan, David Valenzuela-Galvan,Ulysses Paulino Albuquerque, Francisco Reyes-Zepeda,Leonardo Uriel Arellano-Mendez, Arturo Mora-Olivo,and Luis-Bernardo Vazquez

Abstract

From local level ethnobiological research, patterns have been identified in the relationships between humangroups and natural resources. Although these patterns are consistent, they are unknown at a widerspatiotemporal scale, as well as the variables and the causal mechanisms that originate them. One of thefactors that could be influencing the lack of study of social-ecological patterns is the ignorance of newmacro-scale analysis perspectives; as well as the absence of a semantic, conceptual, and analytical framework.For this reason, it is proposed to establish a semantic-conceptual framework of areas in which ethnobiologycan be developed at a macro-scale, which is the application of meta-analysis and the development of macro-ethnobiology. Both perspectives develop larger-scale research (space-time) and are based on the analysis oflocal information (primary information), identify variables, use statistical analysis, and determine processesand patterns by analyzing data heterogeneity. However, both disciplines have different goals, as well as theuse of analysis tools. For the adequate development of any of these two approaches in ethnobiology, it isessential to conceptually know the discipline, select the primary information under quality criteria, fulfillwith the theoretical assumptions of statistical tests, make an adequate interpretation of data variation andhave the support of experts. It is not about proposing new disciplines, but broadening the study approach ofethnobiology, revaluing primary information, analyzing variables together and identifying social-ecologicalprocesses and patterns. We consider that on a broader scale, the analysis is workable for the understandingof social-ecological relationships.

Key words Ethnobiology, Meta-analysis, Macro-ecology, Social-ecological relationships

1 Introduction

Ethnobiology is a multifactorial and interdisciplinary research field[1] which seeks to understand the relationship of cultural, social,biological, and environmental factors [2] by obtaining and

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology,Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_10,© Springer Science+Business Media, LLC, part of Springer Nature 2019

127

accumulating data that can be studied at different spatiotemporalscales; allowing for the identification of social-ecological patterns.

From ethnobiological research, social-ecological patterns havebeen identified at the local level, for example at the level of tradi-tional classification [3–7], plant species domestication and manipu-lation [8, 9], the use of wildlife [10] and edible fungi [11], amongothers. However, although such patterns are evident at a local level[12, 13], few larger scale studies analyze them.

Ethnobiological data study at different spatiotemporal scalesallows to define the social-ecological patterns, as well as the vari-ables that originate them. For example, Molares and Ladio [14]study Mapuche ethnobotany (Argentina and Chile) demonstratingthat there is a set of common knowledge, but with through timecultural erosion. One of the identified social-ecological patterns isthat of biocultural diversity, recognized as the spatial co-occurrencebetween biological, cultural, and linguistic diversity [15–17],which has been related to the Rapoport rule as a statistical explana-tion between these similarities [18] generating an overlappingamong the zones with the greatest biodiversity and “hotspots”conservation priority, and the most diverse cultural regions of theplanet [19].

Other data on social-ecological patterns are:

I. Human populations genetic variation as an effect of geo-graphic isolation and dynamics [20].

II. Evolutive and adaptive processes on geographic distributionand dynamics of language generated by migrationphenomena [21].

III. The support given by natural resources to the development ofhuman societies complying with the laws of physics andenergy [22].

IV. Biodiversity loss and the disproportionate growth of humansocieties with an effect of ecosystem homogenization[23–25].

V. Current distribution modification of some species due toanthropogenic factors [26].

VI. Influence of macro-ecological patterns in agricultural settle-ment systems [27].

VII. Or the biophysical constraints of land on development, sus-tainable consumption and its effect on macro-economics[28–32].

The identification of many of the aforementioned patterns ismainly due to approaches from other research disciplines differentfrom ethnobiology, especially from human macro-ecology. How-ever, the analysis of this type of interrelations is viable from ethno-biology; because it is a growing, multidisciplinary orderliness,

128 Tania Vianney Gutierrez-Santillan et al.

combining both biological and cultural information. This leads totaking concepts and methods in order to generate new theoreticalbases [33], as well as to restructure its approach and strengthen aresearch program not yet completed [2]. And it is one of the mostpromising alternatives, for its conceptual and methodological con-struction, adopting procedures already in use in consolidated fields,such as ecology [34] and also studying in detail the already accu-mulated (ethnobiological) data set, which can be analyzed from themeta-analytical or macro-ethnobiological approach for the under-standing of social-ecological patterns.

As evidence of conceptual growth at different spatiotemporalscales of ethnobiology, we can see that new research perspectiveshave emerged, such as:

I. Evolutionary ethnobiology (EE) which studies the history ofpatterns between human behavior and biological resources[2, 35].

II. Niche construction theory (NCT) as an integrating scenariofor studies that investigate the effect of human activities on theenvironment [36].

III. Macro-ethnobiology as a macroscopic statistical analysis forphenomena that tend to repeat in different places [12].

IV. Or the application of meta-analysis in the evaluation of tradi-tional knowledge [37].

Therefore, we will focus on two of these approaches: meta-analytical and macro-ethnobiological, contributing with a concep-tual framework that allows for ethnobiological analysis at otherscales and with it the identification of processes, patterns, andsocial-ecological variables that underlie them; as well as its consoli-dation and development.

2 Application of Meta-Analysis or Meta-Analytical Approach in Ethnobiology

Albuquerque and Medeiros [12] propose macro-ethnobiology as aresearch stream focused on macroscopic level study approach,focusing its analysis on the statistical understanding of social-ecological phenomena, through meta-analysis application. How-ever, the term macro-ethnobiology may cause confusion if it isrelated to macro-ecology, because they are two totally differentapproaches and analyses.

Therefore, it is suggested for the general framework of itsconceptualization to be the application of meta-analysis or themeta-analytical approach of ethnobiology. Having as main goal todevelop an integrative research by combining disparate researchcomponents (concepts, methods, and data) that is, by adding pri-mary information (previous works) for the construction of large

The Spatiotemporal Scale of Ethnobiology: A Conceptual Contribution in the. . . 129

data sets (“big-data”), characterized by presenting high levels ofcomplexity, diversity, and heterogeneity. These large data sets pres-ent variables which, quantitatively analyzed, based on the a prioriconstruction of hypotheses and through systematic reviews andmeta-analyses, explain processes and patterns.

Systematic reviews are used in the synthesis of informationguided by a predefined research question or by a previously delim-ited problem. They use simple methods to evaluate and filter infor-mation, creating a replicable review [38] but which is generallyqualitative, although they can also include statistical analyses andshould show clarity in the selection criteria for the included studies.Systematic reviews often focus on defining a general research land-scape [39]. However, they may present limitations to contrast thefound evidence, in order to generalize processes and patterns or toidentify information gaps ([39, 40]; Fig. 1).

In contrast, meta-analyses are based on sophisticated statisticalanalysis procedures, which bring benefits to the understanding ofthe development of the research disciplines in which they have beenapplied [41]. These integrate multiple independent studies, quan-tify effects or describe processes structure, through large data setsvariation. They are recognized for increasing confidence and datasynthesis, as well as identifying information gaps ([40–46]; Fig. 1;Box 1). They are used in large-scale patterns determination, allow-ing for the construction of generalizations and evidence-basedassumptions [41]. It is also considered that they generate transfor-mative research, because the solidity patterns of the integrated dataare able to identify causal factors [39].

Fig. 1 General schematization of systematized reviews and meta-analysis. I. Systematic review. II. Meta-

analysis


Box 1 Generalities to Be Considered in the Applicationof Meta-Analysis in Ethnobiological Researches:

Meta-analytical approach development

I A priori hypothesis or delimited problem: General and wide questionsshould be avoided. Instead, questions should be concrete and bebased on a previous review of data availability. They should describe achallenge that can be addressed with the concentrated effort of asmall working group

II Primary information or literature inclusion: A thorough literaturereview should be carried out. In addition, some authors recommendincluding only literature from impact factor journals in order to avoidbias in the data analysis. However, due to the nature of“ethnodisciplines,” characterized by multiple methodologies ingenerating primary information, it is possible to be flexible andinclude information that is available in libraries, or that does not havean impact factor, or that take advantage of high accessibility to onlinedocuments. Much of this information has gone through a rigorousprocess, for example, establishment of research objectives,monitoring of a methodological framework in its development andhas been reviewed by expert academics. However, we do not consideradequate for inclusion information derived from sources such asabstracts from congresses or posts on personal websites

III Inclusion criteria: To provide greater methodological robustness andavoid biases in the inclusion of primary information, search filtersmust be established, for example, a set of keywords

IV Variables or variable coding: These depend directly on the researchquestion and on the available information, since sometimes the primarysources of information do not use the same methodology. If so, acategorization framework of variables can be established to homogenizetheprimary data. The categorizationof variables should corroborate theinfluences of the primary information on the processes or patternssought. It is essential to take into account, when categorizing thevariables, that the primary information data are all accessible

V Effect size or data heterogeneity: In order to integrate the results of theprimary information, an indicator applicable to all independentresults must be defined. This reflects the magnitude of therelationship among the involved variables. Different indices can beused; in this way the primary information is represented in the meta-analysis by an index of the effect size

Statistical analysis and its interpretation: Descriptive, parametric,nonparametric, and even multivariate statistics can be used. Forethnobiological data, since they usually do not fulfill the norms ofdata normality, the application of nonparametric tests isrecommended. It is indispensable to consider the application of thestatistical tests to comply with the theoretical suppositions

VI Processes and patterns: The obtained results must answer the researchobjective, focusing on the a priori hypothesis, on the processes ortrends that were expected, or on those that the data reflect


Meta-analysis application is new and robust; however, it hasthe disadvantage of overestimating or underestimating results ifcriteria are not met during the primary information selection,data validation, theoretical assumptions of chosen statisticaltests, or because of an inadequate interpretation of these([42, 43, 47, 48]; Box 2). To minimize this effect, it is proposedto standardize the primary data search methods as a qualitycontrol, establishing limitations during primary informationselection, as well as to evaluate data variation through heteroge-neity tests and to fulfill theoretical assumptions of the statisticaltests ([46, 49]; Box 3).

Box 2 Criticisms on Ethnobiology Meta-AnalysisDevelopment and Its Similarity with Other Disciplines:

General critics on ethnobiology applied meta-analysis

I Effect size overestimation: This happens when including primaryethnobiological information published with negative data or in favorof the prevalence of some paradigm. This effect can be minimized byconducting a systematic and controlled review

II Heterogeneous data inclusion: It depends on the similarity amongethnobiology studies so they are significant when combined, inethnobiology there is usually a variety of ethnographic samplingtypes, informants, ethnographic tools and in the ethnospeciesidentification at a taxonomic level. These barriers can be passed byapplying hierarchical methods

III Poor quality studies inclusion: When adding studies which do not fulfilthe minimum methodological criteria or that the parameters havenot been adequately measured

IV Variable correlation (co-variables): it is a variable that is not controlledin the data taking; it shows a high correlation with the dependentvariable, and therefore the higher the correlation value, the greaterthe error

Meta-analysis application in ethnobiology is justified by thecontribution and growth of research at local, regional and globallevels in most of the ethnobiological sub disciplines; in the meth-odological research standardization, in the combination of bothcultural and biological data, as well as in the availability and accessto online publications. However, its performance will dependdirectly on the research question or the raised a priori hypothesis.Therefore, we propose to design protocols in which it is establishedthat the data necessary for its application are available in the primaryinformation.


The variables establishment must be focused on phenomenaexplanation as a result of social-ecological characteristics andinteractions [12], in turn the variables are integrated by datasets, which are the basis for the application, development andsuccess of the meta-analysis. However, primary information inethnobiology does not exclude methodological problems, asseen in other areas [39, 41]. One of the main problems is itsorigin, since these data come from both qualitative and quantita-tive research, they have been obtained frommultiple ethnographicand biological methods, gathered from a variety of ethnographictools, analyzed or not by means of some statistical or multivariateanalysis.

Box 3 Primary Information Selection Criteria and Meta-Analysis Data Treatment:

Criteria

I Primary information standardization: Set of key words [46], it ispossible to include the sets that are considered necessary

l Framing the discipline (e.g., ethnosciences)l Defining the object of study (e.g., taxonomic group, ethnic group)l Central research theme (e.g., traditional knowledge, classificationsystems, traditional medicine, perception, management)l Geographic scale (e.g., local, regional, global)

II Data heterogeneity: Analyzing the null hypothesis that the includedstudies are evaluating the same effect* Cochran Q: it is a nonparametric statistical test, which examineswhether k treatments have identical effects [50]l I2: Provides a measure of the inconsistency degree in the studies’results [38]

III Bias evaluation: The primary data contribution should preferably beavailable in Web of Science [44]

l At indexed journals [43]l Publications preferably in English because it is the universallanguage of science [43]l Gray literature inclusion (congresses, theses, briefs) can generatebiases in the conjunction of big-data [43]. However, it can beconsidered as long as criteria are established for its inclusion and thatthe necessary information is available in each one of the researchesl Availability of online publicationsl That all the included studies have similar characteristics or that theyevaluate the same effect

Sometimes the variables can be integrated from the primaryinformation and in other occasions we could opt for their coding.Therefore, variables may be numerical or categorical, dependent orindependent, depending on the trend used to evaluate. In the case


of categorical variables, these can be coded by assigning an ascend-ing numerical value by importance of the subcategories that makeup the variable, where the values depend directly on the subcate-gories amount; or by ordering them randomly or alphabetically. Itis important not to attribute more or less relevance to any subcate-gory, in order to reduce the bias in the value assignment.

Despite the methodological problems that may arise during thedevelopment of the meta-analytical approach in ethnobiology, thebenefits of its application are greater allowing for the establishmentof validated protocols, randomized and controlled trials, evaluationof random data, sensitivity, and identification of heterogeneityfactors (biological, methodological, social, cultural, economic,etc.) in the analysis [43]. It also allows for framing researches atan a priori assumption or hypothesis, and that the studies arereplicable. It also contributes to the identification of informationgaps, consolidating the critical recommendations making in favorof the maturation of ethno disciplines.

However, it should not be forgotten that the development ofthe meta-analytic approach in ethnobiology is complex due to theprimary data nature, mainly because of the variety of methodsapplied for its generation. Therefore, it is essential to recommendthe ethnobiological community to work under standardized meth-ods in the generation of primary information, as well as to establishresearch agendas and networks at a regional and international level.

3 Macro-Ethnobiology

The comparison at different spatiotemporal scales of social-ecological relationships has theoretical and practical relevance forethnobiology. Its systematic study helps to understand the princi-ples that underlie between human beings and their environment[2], in addition to the increasing concern from ecologists, conser-vation biologists, and macro-ecologists to integrate large-scale ana-lyses of cultural, social, and economic factors [12], mainly toevaluate the human impact and influence on biodiversity, and gen-erate adequate conservation strategies [22, 28–30, 34, 51–55].

This approach has been addressed by crossing the boundariesbetween natural and social sciences, through human macro-ecology; focused on the study of the interactions between humangroups and the environment at different spatiotemporal scales,which binds small-scale interactions by identifying emerging pat-terns and their underlying processes; using the same macro-ecological conceptual framework, its analytical rigor, methodologi-cal approach, and technological tools [29, 30]. In turn, humanmacro-ecology can use ethno biological concepts and data to


incorporate social-ecological factors in greater detail, making aconjunction between both disciplines.

Therefore, we can talk about macro-ethnobiology just as longas, besides being based on the principles of human macro-ecology,its interest is to study the statistical properties of a great amount of“ethnobiological particles” (ethnobiological data at a local level)comparable at any level of organization [56]. Where the emergentproperties of the conjunction of a large number of “ethnobiological particles” are described in the large-scale analyses [57],thus evaluating the complete system (Fig. 2).

Multispecific methods have been designed to understand theprocesses behind the patterns. In addition, one of the currentprerogatives of macro-ecology is to create networks amongresearchers [58] with the goal of developing methods and conceptsfor evaluating macro-ecological patterns with current biotic andabiotic conditions [57], emphasizing diversity analysis and its con-servation [59] in which it is essential to include its relationship withhuman groups [51]. This type of analysis is possible thanks to theincrease in data accumulation and informatics resources [60].

In the main, macro-ecology studies the patterns expressed byecological systems through extensive spatial and temporal scales, bystatistically analyzing the processes that determine these patterns([56, 61–64]; Box 4), by emphasizing central points such as(a) integration of the past to current macro-ecological patterns,(b) explicit consideration of local patterns that lead to observedlarge-scale patterns, (c) large-scale data dependence and their qual-ity; and (d) statistical analysis sophisticated methods for explainingthe inherent bias in large-scale sampling [65].

Fig. 2 Macro-ethnobiological approach spatiotemporal scales. (a) Space

(I. Global scale, II. Regional scale; and III Local scale). (b) Time (t ¼ present,

"t ¼ past, +t ¼ future)


Frommacro-ecological perspective, the influence of humans onthe environment, climatic changes produced by anthropogenicactivities; as well as biodiversity loss due to pollution, land usepractices, and ecosystem fragmentation have been studied[30, 57]. Although there is a variety of macro-ecologicalapproaches, these studies do not explicitly distinguish human activ-ities as processes that can give shape or cause patterns variation,such omission can be an error [51]. Since in macro-ecology it hasbeen little studied, the influence of the environment on humangroups, the biotic and abiotic conditions of culture, society,demography, health, or on the use of natural resources or at aneconomic level [30] it is in here where linking with ethnobiologycan contribute significantly, by generating data on social-ecologicalrelationships at the local level.

Box 4 Macro-Ecology:Macro-ecology studies the relationship between organisms andtheir environment, characterizing and explaining organizationpatterns such as distribution, abundance, and diversity; to ana-lzse processes that occur at a regional, global, and/or temporallevel [61–63, 66–68]. It emphasizes its research in the quest foremerging statistical patterns [29, 69, 70] seeks to deepen theknowledge about the structure and functioning of ecologicalsystems [63] characterizing its study in two aspects: large scaleand multispecificity [65]. It is a discipline that answers hypoth-eses about systems which are too large to be manipulated experi-mentally [61] providing new knowledge and ways to understandthem [22, 30].

In its beginnings, macro-ecology based its research on thecorrelative approach, associating a response variable (speciesrichness) and a predicting variable (environmental, geographic,ecological variable, etc.). A clear example is the analysis of thelatitudinal gradient/species richness [29, 68, 69], the distribu-tions of the ecological attributes as a way of understanding thedistributions causal processes [72] and the covariation amongattributes [61]. However, it is a discipline characterized by con-stant revolutionizing without losing interest in determining eco-logical patterns and the causal variables that generate them.Currently, based on large datasets management, simulationmodels and technological implementations have generated newresearch trends, such as macro-evolution [73–75], applicationand development of the niche concept [76–78], phylo-macro-ecology [79], metabolic theories development [80], unifyingtheory [81], beta diversity analyses [82, 83], and sustainabilityand human macro-ecology [22, 30], among other approaches.

A broader understanding of macro-ecology, its objectivesand its methods helps to consider large-scale questions and

(continued)


Box 4 (continued)research [84], responding every time to more complex ques-tions, one of them being the contribution to one of the greatestchallenges of the twenty-first century, to ensure a sustainablefuture for humanity, by combining cultural evolution as a mainhuman characteristic, related to the role of energy availability andnatural resources [29].

Macro-ecology is a discipline worldwide characterized forhaving a great development, until reaching today’s situation[65]. As a discipline that counts with more and more researchgroups that contribute to its study, due to its spectacular advancein the generation and availability of information [85]. Proposingnew research questions, advancing in the understanding of theprocesses and mechanisms that underlie these patterns [29].

A macro-ethnobiological pattern recognized from the ethno-biological framework and studied through humanmacro-ecology isthat of biocultural diversity, understood as the spatialco-occurrence between the areas of greatest biological, cultural,and linguistic richness, which are located in the intertropical regionthroughout the planet [15–17, 55, 86–88]. This has allowed us toidentify that these regions have high levels of energy availability,complying with the macro-ecological rule of productivity[89]. Other macro-ethnobiological patterns, are the area–diversityrelationship; since it has been seen that the mountainous areasharbor a high cultural diversity, areas that also have a high biologicaldiversity [15]; or the positive relationship between the regions size(islands) and their linguistic variation [88] as a mechanistic phe-nomenon in the geographical arrangement.

In order to develop the macro-ethnobiological approach it isimperative to consider in its application the search for correspon-dence with some of the macro-ecological rules, from the perspec-tive that we wish to study.

Going into:

I. The species–area relationship, where a positive relationship isestablished between the species richness and the area size;

II. The latitudinal and altitudinal gradients, in the first case wehave seen that there is a greater species richness in areas close tothe tropics, and in the second there is a greater diversity in thenear regions at sea level.

III. The species–diversity habitats relation, which assumes that themore heterogeneous a region is, the greater the biologicaldiversity it will present.

IV. The biodiversity–productivity relationship, which proposesthat the most productive ecosystems will sustain greater


biological diversity; among other described macro-ecologicalrules (Table 1).

This is possible by designing research to assess whether theserules apply in social-ecological relationships.

Exploring if:

I. The bigger the area, the bigger the species use and knowledge.

II. If human groups include more biodiversity in their social-ecological systems by getting closer to the intertropical zones.

III. If people use more resources at a lower altitude.

IV. If human groups in territories with larger environmental het-erogeneity develop larger species use and knowledge.

V. If at more productive regions there is an increase in the tradi-tional systems of biodiversity use and knowledge, among othermacro-ethnobiological patterns (Table 1).

It is important to consider that the suggested macro-ethnobiological patterns are not always fulfilled in the same wayfor all biological groups, since these in turn are determined bymacro-ecological patterns. The exploration of macro-ethnobiological rules is necessary, through the establishment ofmore specific investigations for each biological group and at differ-ent spatial and temporal scales.

Proposing the hypothesis exploration as:

I. In the case of wild fauna there is a greater use of species in thenumber of uses and parts used and their relation with size.

II. For edible fungi there is a greater diversity of species that areharvested in temperate regions (pine, oak, mixed forests) com-pared to tropical areas.

III. Wild flora species with medicinal and edible potential are thosethat have been domesticated the most.

IV. Floristic species that show certain secondary compounds aremore likely to be part of social-ecological systems.

V. Large and medium-sized species have a greater number of usesand parts used, than smaller ones.

In addition, social-ecological systems can be explored by add-ing cultural, social, economic, and environmental variables.

Explaining phenomena like:

I. Human groups belonging to the same linguistic family (cul-tural origin) possess greater similarity in their social-ecologicalsystems.

II. There are convergent patterns of traditional ecological systemsamong culturally unrelated human groups, originated by thebiological characteristics of the species.


Table1

Macro-ecologicalpatternsandexamplesin

whichmacro-ethnobiologicalapproach

researchcanbecarriedout

Macro-ecological

pattern

Description

Suggestedmacro-ethnobiological

patterns

Visualization

Species–area

relation

Speciesrichnessin

anarea

isa

potentialfunctionofthearea

size

Thegreater

theculturalarea,the

greater

bioculturaldiversity

(richnessofknownandused

species)

Latitudinalgradient

Thegreatestspeciesrichnessisfound

inlatitudes

close

totheeq

uator,

establishingthat

aswemove

away

(N/S)thewealthgradually

decreases

Human

groupsestablished

inthe

intertropicalzo

neincludegreater

recognitionanduse

ofdiversity

intheirsocioecologicalsystem

sthan

those

established

inhigher

latitudes

Altitudinalgradient

Thereisgreater

speciesdiversity

ataltitudes

closerto

sealevel,

decreasingas

altitudeincreases

Human

groupsuse

more

resources

when

atlower

altitude

(continued

)


Table1

(continued)

Macro-ecological

pattern

Description

Suggestedmacro-ethnobiological

patterns

Visualization

Species–habitat

diversity

relation

Thegreater

thehabitat

diversity,the

greater

thespeciesrichness,a

response

tolandscapeheterogen

eity

Human

groupswhose

territories

have

greater

environmen

tal

heterogen

eity

willpresentgreater

diversity

ofspeciesuse

and

knowledge

Biodiversity–productivity

relation

Thehigher

theen

ergyflow

rate

ina

system

(productivity),thegreater

thebiologicaldiversity

I.Theareaswithgreatestbiocultural

diversity

arelocatedin

theareas

withthehighestproductivityonthe

planet

II.In

regionswithhigher

productivity

thereisan

increase

intraditional

system

sofknowledgeanduse

of

biodiversity

Bodysize

distribution

More

smallbodysize

specieshave

beendescribed

inrelationto

large

size

species

Thereisagreater

number

ofspecies

withaculturaliden

tifier

inspecies

ofmed

ium

andsm

allsize

compared

tolargesize

species


Speciesabundance

distributionrelation

Localspeciesabundance

increases

withwidedistribution

I.Culturalrecognitionat

theregional

levelincreaseswithspecies

distribution

II.Specieswithrestricted

distributionshavealocalcultural

assignmen

tIII.Specieswithbroad

distribution

ranges

havegreater

cultural

relevance

than

those

withsm

alleror

restricted

distribution

Speciesabundance–body

size

relation

Speciesabundance

decreases

with

bodymassam

ongspecieswithin

anygreat

taxo

n

Speciesculturalassignmen

tincreases

inrelationto

theirbodysize

Theoriginalidea

was

designed

byStephen

sandcollaborators

[71],whoexplore

themacro-ecologicalrulesthat

operateforwildandparasiticspecies


III. Species traditional use and knowledge at ethnohistorical docu-ments prevail at some regions in the present.

IV. Current macro-economy and globalization phenomena gener-ate cultural homogenisation conditions.

V. Traditional social-ecological systems favor biodiversityconservation.

In addition to considering compliance with macro-ecologicalrules, attention must be paid to the data set and the analysis vari-ables. Macro-ecology bases its studies on geography and demogra-phy, a link between these two variables is the correlation betweenspecies diversity in the sites and the average range of species thatoccur in there; reflecting mathematical and biological relationships,being sites diversity and species distribution the fundamental pieces[90]. Similar attributes are found in the ethnobiological data, tak-ing as analysis units the species lists published in the ethnobiologicalworks, with which it is possible to generate incidence matrices(presence–absence) constituting the integrating variables withsites and species descriptors. Regarding the variables, environmen-tal, geographical, and ecological variables can be used, to whichcultural, social, and economic variables can be added, taking carethat these are not correlated.

By combining data and variables from humanmacro-ecology, ithas been suggested to analyze patterns such as the energy exchangebetween humans and the biophysical environment, human nutri-tion ecology, life history, geographical space use, human populationstructure, disease ecology, industrial and urban systems [30]. How-ever, we still need to include some fundamental aspects such as thetraditional systems of knowledge, use and management of thespecies, because it is considered that there is little informationabout it; but these variables can be included from the macro-ethnobiological perspective. As a central point of research, it con-siders that the Earth’s most biodiverse areas are occupied by nativegroups [15–17, 87].

4 Why Asking Research Questions for Meta-Analytical and Macro-EthnobiologicalApproach Development?

For the success and good development of the meta-analytical andmacro-ethnobiological approach, it is essential to draw a frame ofreference. This type of exercise has been applied in ecology byseeking to list its main challenges and means to solve them[91–93]. This is possible by highlighting key issues, designing aseries of questions that identify ethnobiological areas that have thepotential to significantly advance and provide a working agenda;emphasizing that the main objective of these research approaches isto determine processes, patterns, and variables of the relationships


between human groups and biological diversity; analyzing theinfluence of those relationships on ecosystems and species conser-vation, and community development; integrating the ecological,environmental, social, cultural, and economic problems.

The goal of designing a framework is to generate importantquestions with answers for the different ethnobiological disciplines.General and broad questions should be avoided; instead it is recom-mended to develop questions that describe a challenge that can beaddressed with a focused and concentrated effort of a small groupof researchers or through a research program receiving adequatefinancial support.

The proposal questions must be rigorous, democratic, andtransparent, without the aim of favoring a particular researchgroup, and lacking a desire to develop only one or another ethno-biological discipline, as well as to choose to work with a specifichuman group or geographic region. To carry out this process ofquestion development and selection, one could start, for example,with a search for international authors inviting them to join acollaborative working group. This search would focus on research-ers who have a greater number of citations, the editors of importantjournals in the area, as well as a representative from each of thecountries that have the greatest contributions to the discipline at aninternational level. The search should be seeking a balanced repre-sentation of researchers who work on different ethnobiologicalareas.

It is also important to look for financing at institutional andgovernmental levels, and also to establish collaborations with othernonethnobiological disciplines with the purpose of creating a work-ing group and collaborative networks that seek to promote meet-ings in which the relevant topics and possible issues are discussed.As well as the selection of thematic areas of predominant researchthat reflect the ethnobiological context and that generate a criticaldiscussion about the possible results, in order to reformulate thequestions and approaches. The questions should take into consid-eration their expected importance and impact. For example, nowa-days some of the premises of ecology and ethnobiology areconservation, sustainable management and development, and inte-grating social actors. This is due to the fact that environmental andcultural changes are strongly affecting local communities andbiodiversity.

It is important to let the ethnobiological community know thatnew research perspectives, in this case the meta-analytical andmacroethnobiological approach, are not proposed as new ethnobi-ological subdisciplines. Rather, they seek to have a broader view ofthe variables, processes, and patterns that are integrating the disci-pline. Thus, conceptual and methodological gaps are explored,designing inclusive research programs of a large scientific commu-nity that significantly contributes to their scientific maturity(Table 2).


References

1. Wolverton S (2013) Ethnobiology 5: interdis-ciplinarity in an era of rapid environmentalchange. EBL 4:21–25

2. Albuquerque UP, Ferreira-Junior W (2017)What do we study in evolutionary ethnobiol-ogy? Defining the theoretical basis for aresearch program. Evol Biol 44(2):206–215

3. Berlin B (1973) Folk systematics in relation tobiological classification and nomenclature.Annu Rev Ecol Evol Syst 4:259–271

4. Berlin B, Breedlove DE, Raven PH (1973)General principles of classification and nomen-clature in folk biology. Am Anthropol75:214–242

5. Berlin B, Boster JS (1981) The perceptualbases of ethnobiological classification: evidencefrom Aguaruna Jıvaro ornithology. J Ethnobiol1(1):95–108

6. Brown CH (1985) Mode of subsistence andfolk biological taxonomy. Curr Anthropol 26(1):43–64

7. Hunn E (1982) The utilitarian factor in folkbiological classification. Am Anthropol 84(4):830–847

8. Caballero J, Casas A, Cortes L et al (1998)Patrones en el conocimiento, uso y manejo de

plantas en pueblos indıgenas de Mexico. EstudAtaca 16:181–195

9. Casas A, Parra F, Blancas J (2015) Evolution ofhumans and by humans. In: Albuquerque UP,Medeiros PM, Casas A (eds) Evolutionary eth-nobiology. Springer, New York, pp 21–36

10. Alves R (2012) Relationships between faunaland people and the role of ethnozoology inanimal conservation. Ethnobiol Conserv 1(2):1–69

11. Boa E (2004) Non-wood forest product 17:wild edible fungi. A global overview of theiruse and importance to people. Food and Agri-culture Organization of the United Nations,Rome, p 148

12. Albuquerque UP, Medeiros P (2012) System-atic reviews and meta-analysis applied to ethno-biological research. Ethnobiol Conserv 1(6):1–8

13. Campos J, Sobral A, Silva J et al (2016) Insu-larity and citation behavior of scientific articlesin young fields: the case of ethnobiology. Scien-tometrics 109(2):1037–1055

14. Molares S, Ladio A (2012) The usefulness ofedible and medicinal fabaceae in Argentine andChilean Patagonia: environmental availability

Table 2

Questions examples for meta-analytical and macro-ethnobiological approach

Focus Questions

Meta-analysis Is it possible, with the availability of “big-data” primary information, the developmentof meta-analytical approach?

Does the meta-analysis application allow for the identification of information gaps?Critically contributing to its scientific consolidation

Is a methodological standardization and a quantitative growth of ethnobiologypossible?

Which are the most culturally relevant species at a regional and global level?What should be the central lines of research in ethnobiology, facing the acceleratedloss of biological and cultural diversity?

What is the difference in the discipline growth and maturation between the qualitativeand quantitative contributions?

Macro-ethnobiology

What is the relationship between the biocultural diversity loss and the ecosystemshomogenization?

What is the effect of overexploitation of natural resources in the different indigenousregions at a regional and global level?

Can biocultural patterns be identified by applying the macro-ethnobiologicalapproach?

Is the biodiversity management at indigenous regions optimal?

Shown questions do not necessarily indicate an importance order, some may contribute disciplines development in a

theoretical, conceptual, methodological, practical, or developmental way


and other sources of supply. Evid Based Com-plement Altern Med 1:1–12

15. Stepp JR, Castaneda H, Cervone S (2005)Mountains and biocultural diversity. Mt ResDev 25(3):223–227

16. Loh J, Harmon D (2005) A global index ofbiocultural diversity. Ecol Indic 5:321–241

17. Harmon D, Loh J (2010) The index of linguis-tic diversity: a new quantitative measure oftrends in the status of the world’s languages.LD&C 4:97–151

18. Gavin MC, Stepp JR (2014) Rapoport’s rulerevisited: geographical distributions of humanlanguages. PLoS One 9(9):e107623

19. Gorenflo LJ, Romaine S, Mittermeier R et al(2012) Co-occurrence of linguistic andbiological diversity in biodiversity hotspotsand high biodiversity wilderness areas. ProcNatl Acad Sci 109(21):8032–8037

20. Moreno-Estrada A, Gignoux CR, Fernandez-Lopez JC et al (2014) Human genetics. Thegenetics of Mexico recapitulates Native Ameri-can substructure and affects biomedical traits.Science 344(6189):1280–1285

21. Mace R, Holden CJ (2005) A phylogeneticapproach to cultural evolution. Trends EcolEvol 20(3):116–121

22. Burger JR, Allen CD, Brown JH et al (2012)The macroecology of sustainability. PLoS Biol10(6):e1001345

23. Vazquez L-B, Gaston KJ (2006) People andmammals in Mexico: conservation conflicts ata national scale. Biodivers Conserv 15(8):2397–2414

24. Vellend M, Verheyen K, Flinn KM et al (2007)Homogenization of forest plant communitiesand weakening of species-environment rela-tionships via agricultural land use. J Ecol 95(3):565–573

25. Cardinale BJ, Duffy JE, Gonzalez A et al(2012) Biodiversity loss and its impact onhumanity. Nature 486:59–67

26. Santini L, Gonzalez-Suarez M, Rondinini Cet al (2017) Shifting baseline in macroecology?Unravelling the influence of human impact onmammalian body mass. Divers Distribut 23(6):640–649

27. Tao T, Abades S, Teng S et al (2017) Macro-ecological factors shape local-scale spatial pat-terns in agriculturalist settlements. Proc R Soc284(1866):20172003

28. Brown JH, Burnside WR, Davison AD et al(2011) Energetic limits to economic growth.Bioscience 61(1):19–26

29. Brown JH, Burger JR, Burnside WR et al(2014) Macroecology meets macroeconomics:

resouce scarcity and global sustainability. EcolEng 65:24–32

30. Burnside WR, Brown JH, Burger O et al(2012) Human macroecology: linking patternand process in big-picture human ecology. BiolRev 87(1):194–208

31. Mace GM (2012) The limits to sustainabilityscience: ecological constraints or endless inno-vation? PLoS Biol 10(6):1–2

32. Ehrlich PR, Ehrlich AH (2013) Can a collapseof global civilization be avoided? Proc R Soc280:20122845

33. Albuquerque UP, Hanazaki N (2009) Fiveproblems in current ethnobotanical researchand some suggestions for strengthening them.Hum Ecol 37:653–661

34. Saslis-Lagoudakis CH, Clarke AC (2013) Eth-nobiology: the missing link in ecology andevolution. Trends Ecol Evol 28(2):67–68

35. Albuquerque UP, Ferreira-Junior WS, SantoroFR et al (2015) Niche construction theory andethnobiology. In: Albuquerque UP, MedeirosPM, Casas A (eds) Evol Ethnobiol. Springer,New York, pp 73–87

36. Albuquerque UP, Santos-Goncalves PH, Fer-reira-Junior W et al (2018) Humans as nicheconstructors: revisiting the concept of chronicanthropogenic disturbances in ecology.PECON 16(1):1–11

37. Torres-Avilez W, Medeiros P, Albuquerque UP(2016) Effect of gender on the knowledge ofmedicinal plants: systematic review and meta-analysis. Evid Based Complement Altern Med2016:6592363

38. Higgins JPT, Green S (2009) Cochrane hand-book for systematic reviews of interventions.Ver. 5.0.2. Wiley, Hoboken, NJ

39. Lortie CJ (2014) Formalized synthesis oppor-tunities for ecology: systematic reviews andmeta-analyses. Oikos 123(8):897–902

40. Egger M, Smith GD (1997) Meta-analysis:potentials and promise. BMJ 315:1371–1374

41. Stewart G (2009) Meta-analysis in appliedecology. Biol Lett 6:78–81

42. Arnqvist G, Wooster D (1995) Meta-analysis:synthesizing research findings in ecology andevolution. Trends Ecol Evol 10(6):236–240

43. Gates S (2002) Review of methodology ofquantitative reviews using meta-analysis inecology. J Anim Ecol 71:547–557

44. Kueffer C, Niinemets U, Drenovsky RE et al(2011) Fame, glory and neglect in meta-analyses. Trends Ecol Evol 26(10):493–494

45. Koricheva J, Gurevitch J (2014) Uses andmisuses of meta-analysis in plant ecology. JEcol 102:828–844


46. ArchMiller AA, Bauer EF, Koch RE et al(2015) Formalizing the definition of meta-analysis in molecular ecology. Mol Ecol 24(16):4042–4051

47. Peterman RM (1995) Statistical power ofmethods of meta-analysis. Trends Ecol Evol10(11):460

48. Higgins JPT, Thompson SG, Deeks JJ et al(2009) Measuring inconsistency in meta-analyses. BMJ 327:557–560

49. Beninde J, Veith M, Hochkirch A (2015) Bio-diversity in cities needs space: a meta-analysis offactors determining intra-urban biodiversityvariation. Ecol Lett 18(6):581–592

50. Zar JH (2010) Biostatistical analysis, 5th edn.Pearson Prentice Hall, Upper Saddle River,p 944

51. Gaston KJ (2004) Macroecology and people.Basic Appl Ecol 5(4):303–307

52. Gaston KJ (2005) Biodiversity and extinction:species and people. Prog Phys Geogr 29(2):239–247

53. Gaston KJ (2006) Biodiversity and extinction:macroecological patterns and people. ProgPhys Geogr 30(2):258–269

54. Gaston KJ, Evans KL (2004) Birds and peoplein Europe. Proc R Soc 271(1548):1649–1655

55. Gavin MC, McCarter J, Mead A et al (2015)Defining biocultural approaches to conserva-tion. Trends Ecol Evol 30(3):140–145

56. Brown JH (1999) Macroecology: progress andprospect. Oikos 87:3–14

57. Kuhn I, Bohning-Gaese K, Cramer W et al(2008) Macroecology meets global changeresearch. Glob Ecol Biogeogr 17(1):3–4

58. Keith SA, Webb TJ, Bohning-Gaese K et al(2012) What is macroecology? Biol Lett8:904–906

59. P€artel M, Bennett JA, Zobel M (2016) Macro-ecology of biodiversity: disentangling local andregional effects. New Phytol 211(2):404–410

60. Maldonado C, Molina CI, Zizka A et al (2015)Estimating species diversity and distribution inthe era of big data: to what extent can we trustpublic databases? Glob Ecol Biogeogr24:973–984

61. Brown JH, Maurer BA (1989) Macroecology:the division of food and space among specieson continents. Science 243(4895):1145–1150

62. Brown JH (2003) Macroecologıa. Fondo deCultura Economica. Distrito Federal, p 397

63. Gaston KJ, Blackburn TM (2000) Pattern andprocess in macroecology (eds). Blackwell Sci-ence, Malden, p 377

64. Blackburn TM, Gaston K (2002) Macroecol-ogy is distinct from biogeography. Nature418:723

65. Beck J, Ballesteros-Mejia L, Buchmann CMet al (2012) What’s on the horizon for macro-ecology? Ecography 35:673–683

66. Brown JH, Stevens GC, Kaufman DM (1996)The geographic range: size, shape, boundaries,and internal structure. Annu Rev Ecol EvolSyst 27(1):597–623

67. Hawkins BA, Portes EE, Diniz-Filho JA(2003) Productivity and history as predictorsof the latitudinal diversity gradient of terrestrialbirds. Ecology 84(6):1608–1623

68. Koleff P, Soberon J, Arita HT et al (2008)Patrones de diversidad espacial en grupos selec-tos de especies. In: Soberon J, Halffter G,Llorente-Bousquets J (eds) Capital natural deMexico vol I, conocimiento de la biodiversi-dad. Comision Nacional para el Conocimientoy Uso de la Biodiversidad, Distrito Federal, pp323–364

69. Rosenzweig ML (1995) Species diversity inspace and time. Cambridge University Press,Cambridge, p 436

70. Marquet PA (2009) Macroecological perspec-tives on communities and ecosystems. In:Levin SA (ed) The Princeton guide to ecology.Princeton University Press, Princeton, NJ, pp386–394

71. Stephens PR, Altizer S, Smith KF et al (2016)The macroecology of infectious diseases: a newperspective on global-scale drivers of pathogendistributions and impacts. Ecol Lett19:1159–1171

72. Gaston K (1990) Patterns in geographicalranges of species. Biol Rev 65(2):105–129

73. Diniz-Filho JAF, Gouveia SF, Lima-RibeiroMS (2013) Evolutionary macroecology. FrontBiogeogr 5:195–203

74. Bini LM, Villalobos F, Diniz-Filho JA (2014)Explorando patrones en rasgos macroecologi-cos utilizando regresion secuencial de auto-verctores filogeneticos. Ecosistemas 23(1):21–26

75. Villalobos F, Carotenuto F, Raia P et al (2016)Phylogenetic fields through time: temporaldynamics of geographic co-occurrence andphylogenetic structure within species ranges.Phil Trans R Soc A 371(1691):20150220

76. Peterson AT, Ortega-Huerta MA, Sanchez-Cordero V et al (2002) Future projections forMexican faunas under global climate changescenarios. Nature 416:626–629

77. Peterson AT, Soberon J (2012) Species distri-bution modeling and ecological niche


modeling: getting the concepts right. NatConserv 10:102–107

78. Olalla-Tarraga MA, Gonzalez-Suarez M,Bernardo-Madrid R et al (2017) Contrastingevidence of phylogenetic trophic niche conser-vatism in mammals worldwide. J Biogeogr44:99–110

79. Tucker CM, Cadotte MW, Carvalho SB et al(2016) A guide to phylogenetic metrics forconservation, community ecology and macro-ecology. Biol Rev 29(2):698–715

80. Tittensor DP, Enquist B, Worm B (2016) Aneural-metabolic theory of latitudinal biodiver-sity. Glob Ecol Biogeogr 25(6):630–641

81. McGill BJA (2003) A test of the unified neutraltheory of biodiversity. Nature 422:881–885

82. Calderon-Patron J, Moreno M, Pineda C et al(2013) Vertebrate dissimilarity, turnover andnestedness in a highly beta-diverse Region:the role of spatial grain size, dispersal abilityand distance. PLoS One 8(12):e82905

83. Calderon-Patron JM, Goyenechea I, Ortiz-Pulido R et al (2016) Beta diversity in a highlyheterogeneous area: disentangling species andtaxonomic dissimilarity for terrestrial verte-brates. PLoS One 11(8):1–15

84. Blackburn TM (2004) Method in macroecol-ogy. Basic Appl Ecol 5(5):401–412

85. Rodrıguez P, Villalobos F, Sanchez-Barradas Aet al (2017) La macroecologıa en Mexico: his-toria, avances y perspectivas. Rev Mex Biodi-vers 88:52–64

86. Stepp JR, Cervone S, Castaneda H et al (2004)Development of a GIS for global bioculturaldiversity. Policy Matters 13:267–271

87. Skutnabb-Kangas T (2011) Language ecology.In: Ostman JO, Verschueren J (eds) Pragmaticsin practice. John Benjamins Publishing Com-pany, Amsterdam, pp 176–198

88. Gavin MC, Sibanda N (2012) The island bio-geography of languages. Glob Ecol Biogeogr21(10):958–967

89. Gillman LN, Wright SD, Cusens J et al (2015)Latitude, productivity and species richness.Glob Ecol Biogeogr 24:107–117

90. Arita HT, Christen JA, Rodrıguez P et al(2008) Species diversity and distribution inpresence-absence matrices: mathematical rela-tionships and biological implications. Am Nat172(4):519–532

91. Sutherland WJ, Adams WM, Aronson RB et al(2009) An assessment of the 100 questions ofgreatest importance to the conservation ofglobal biological diversity. Conserv Biol23:557–567

92. Sutherland WJ, Freckleton RP, Godfray HCJet al (2013) Identification of 100 fundamentalecological questions. J Ecol 101:58–67

93. Grierson CS, Barnes RS, Chase MW et al(2011) One hundred important questions fac-ing plant science research. New Phytol192:6–12


ulysses paulino albuquerque reinaldo farias paiva de...

Documents